Simulation of Sound Spectra of Complex Didgeridoo Interior Forms
Dr. Frank Geipel
MotivationEvery advanced didgeridoo player will have found that the sound characteristics (toots, timbre, ...) and the playability (back-pressure, responsiveness…) are essentially influenced by the inside form and the material of the instrument. I know many players who are forever searching for a didgeridoo with their ideal sound and playability because of this. Often it’s a very sobering search because very few of the instruments offered on the didgeridoo “market” fully meet one’s expectations. And many of those one-offs that do are also very expensive.
In the didge scene there are opportunities to thoroughly inform yourself about the crafting skills needed to make the instrument. Because I wanted to work with wood, I had the choice between the sandwich method (practised by Eddy Halat, Stefan Thiel, Jan-Ole Haber, Kay Reimer, and others) and the drilling method (practised by Walter Strasser, Johannes Schildkamp and others in several variations). Unfortunately I’ve yet to hear of “trained termites” in central Europe. Interesting though the drilling method practised by a few craft artists is, I opted for the simpler sandwich method because it allows considerably more complex internal forms to be realised. While I was researching the methods I got to know some interesting didgeridoo makers, including the Test-A-Doo experimenter, Kay Reimer, whose acoustic experiments impressed me very deeply. I followed his web instructions to make my own first wooden didgeridoo.
2) Using wood
Unfortunately research on this topic only provides suitable mathematical
solutions for simple cylindrical and exactly conical tubing shapes (formula
sides 1 and 2).
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The methodI searched for a method by which the passive acoustic
properties of more complex didgeridoo internal forms are calculable.
With this method, a didgeridoo is mathematically split
into a finite number of cylindrical and conical pieces. The acoustic
chain matrix in the complex numbers sector can be resolved for thus
modelled inner cavities of didgeridoos, taking into account the uneven
inside walls. In this way one obtains the so-called input impedance
spectra, from which the resonant frequencies of the air column and the
back-pressure of the drone (fundamental tone) and toots (series of
overblows) can be read. By coupling the impedance spectra with the
respective simulated overtone spectra when playing the drone or toots,
one obtains additionally the sound spectra for the drone and the first
toot. These simulated sound spectra match well with the practically
analysable FFT (Fast Fourier Transformation) spectrograms when the
individual instruments are played. Audio frequencies in Hz; The range marked in grey
shows the fundamental tone frequencies in which most didgeridoos
resonate. The following example shows the sound simulation of actual measurements of one of Walter Strasser’s didgeridoos and the accompanying practical analysis of the FFT spectrogram with an FFT analysis programme.
Walter Strasser’s didgeridoo; black:
simulation of the toot sequences (drone and overblows);
Practical analysis of the FFT spectrum when playing the drone; the sound level depicted is a relative logarithmic value expressing the difference between acoustic pressures. However, to interpret these spectra the subjective perception of volume of the concurrently sounding frequencies is important. Without wanting to delve any deeper into that aspect, it can be assumed that from the highest peak (i.e. the loudest frequency) only those frequencies still significantly influence the sound character which are up to about 40 dB below the highest peak. All quieter frequencies are overlaid by the louder ones. That means that for every FFT spectrum there exists a sound level section (green box=, that significantly determines the sound characteristic.
Wave pattern for this didgeridoo
Current outcomes of the project are various prototype software tools
by which, in dependence of complex internal forms, the toot sequences
(drone and overblows) and the sound spectra of the drone and 1st toot
can be simulated/calculated. Presently these tools are to hand as
non-self-explanatory work versions still under development.
Simulation of a didgeridoo with parallel
amplified 4th and 5th harmonic overtone
Using the method developed opens up the
following possibilities:
The simulation of sound spectra of many hundreds of didgeridoo
interiors with a computer makes clear that just small changes of the
inner form can open up a “universe” of possible sound spectra. The
ultimate didgeridoo that realises all possible wishes about sound
characteristics is not calculable. What is possible, though, is an
almost endless variety of didgeridoos with unique sound and playing
qualities.
For anyone with a deeper interest in this theme, I can recommend the book “Das Didgeridoo-Phänomen”. The chapter “Simulation of sound spectra of complex internal didgeridoo forms – Computer Aided Didge (Sound) Design” describes in detail the methodology, the physical correlations and the possibilities for didgeridoo building.
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